Difficulty: Beginner · Last updated: January 2, 2027 · By Mantlr Editorial
Twelve Figma Make examples across categories — what designers and founders have built, what prompted them, and what each reveals about the tool's real range.
Key takeaways
Six things these examples reveal about Figma Make:
1. Make works best on bounded, well-defined product types — pricing pages, dashboards, single-purpose apps
2. Generated apps with strong constraints outperform apps with vague briefs
3. Multi-screen flows work but require iteration discipline; single-screen generation is more reliable
4. Backend-enabled examples (Supabase auth + database) feel meaningfully different from static prototypes
5. Examples that use Make kits look on-brand; examples without kits look like Make's default style
6. The pattern across all examples: front-loaded prompts produce shippable starting points
On this page
- How to read these examples
- Example 1: SaaS pricing page with monthly/annual toggle
- Example 2: Habit-tracking app with backend
- Example 3: Internal admin dashboard
- Example 4: Personal portfolio site
- Example 5: Marketplace browse experience
- Example 6: AI chat interface
- Example 7: Multi-step onboarding flow
- Example 8: Mobile fitness app
- Example 9: Crypto portfolio tracker
- Example 10: Blog and content hub
- Example 11: Booking and scheduling app
- Example 12: Internal HR tool
- What patterns emerge across all 12
- Common pitfalls visible in real-world examples
- Frequently asked questions
- Related articles
The fastest way to understand what Figma Make is actually capable of is to look at real outputs. Not the marketing examples Figma showcases. Real apps designers and founders have built, with the prompts that produced them, with honest notes on what worked and what didn't.
This guide collects twelve examples across categories. Each entry includes the use case, a representative prompt structure, what Make generated well, and what the designer had to iterate on. The goal isn't to give you templates to copy — it's to help you internalize what Make does well and where it struggles, so you can prompt it more effectively for your own work.
If you're new to Figma Make entirely, read What Is Figma Make? first. For prompt engineering specifically, see How to Write Better Figma Make Prompts.
Quick wins
1. Scan the examples that match your use case. The patterns transfer faster than reading abstract guides.
2. Notice the prompt structure in each example — front-loaded context, specific values, defined interactions.
3. Pay attention to "what worked" and "what needed iteration" notes. The honest framing helps calibrate expectations.
How to read these examples
Each example below follows the same structure:
- The use case — what someone built and why
- Prompt structure — the type of prompt that produced the result (paraphrased, not exact transcript)
- What Make generated well — the parts that needed minimal iteration
- What needed iteration — the parts that took follow-up prompts
- Time to shippable prototype — honest estimate of total effort
These aren't fabricated examples. They reflect the patterns Mantlr Editorial has seen across real Figma Make usage over the past year. We've anonymized specifics but the workflow patterns are accurate.
Example 1: SaaS pricing page with monthly/annual toggle
The use case: A founder building a productivity SaaS needed a pricing page to validate willingness-to-pay before any engineering investment.
Prompt structure: Detailed product description, three pricing tiers with prices, monthly/annual toggle requirement, FAQ section, brand color and font specified explicitly.
What Make generated well: The pricing card structure, the monthly/annual toggle with smooth animation, the comparison table beneath the cards, the FAQ accordion behavior.
What needed iteration: Copy refinements (placeholder text felt corporate), spacing tweaks, button hover states.
Time to shippable prototype: 90 minutes.
The pricing page is the prototype-to-validation sweet spot for Make. Bounded structure, well-known conventions, easily testable with users.
Example 2: Habit-tracking app with backend
The use case: A solo designer building a side project — a daily habit tracker with streak counters, partner accountability features, and progress visualization.
Prompt structure: App description, user persona (new parents balancing work and family), screens needed (today view, habits library, partner connection, settings), visual style with specific palette.
What Make generated well: The today view with check-off interactions, the streak counter logic, the habit creation flow.
What needed iteration: The partner accountability feature required significant rework. The backend setup for the user account system needed explicit prompting (Supabase auth + database for habits per user).
Time to shippable prototype: 6-8 hours, including backend setup.
This is the prototype that crosses into "real app" territory. The Supabase integration meant real user accounts, real persistent data, real partner sharing. Make handles this well but with more iteration than static prototypes.
Example 3: Internal admin dashboard
The use case: A product team building a marketplace needed an admin tool for seller onboarding — reviewing applications, approving sellers, flagging suspicious accounts.
Prompt structure: Internal tool framing, target user (operations team), table-heavy layout, filter requirements, action button patterns, status badge system.
What Make generated well: The data table with sortable columns, the filter sidebar, the status badge styling, the bulk action patterns.
What needed iteration: The row-click side panel for full seller details needed multiple iteration cycles to feel natural. The approval workflow modal needed copy refinement.
Time to shippable prototype: 3-4 hours.
Internal tools are Make's quiet strength. The output doesn't need to win design awards — it needs to work for an internal user. Make's defaults are good enough out of the box for utilitarian admin work.
Example 4: Personal portfolio site
The use case: A designer building their personal portfolio with case study depth, contact form, and blog.
Prompt structure: Portfolio site, designer profile, sections (work, about, contact, blog), visual style description (minimal, dark theme, monospace headers), specific projects to feature.
What Make generated well: The work index layout, the case study template structure, the about page typography, the contact form.
What needed iteration: Case study pages needed individual attention — Make's first generation produced templates but the actual case study content required manual entry. The blog template needed significant copy work.
Time to shippable prototype: 4-5 hours for the framework, plus content entry time.
Portfolios are a good Make use case because the structure is bounded. The harder work is the case study content itself, which Make can't write for you.
Example 5: Marketplace browse experience
The use case: A founder validating a marketplace concept needed a working browse experience with filters, product cards, and a seller detail view.
Prompt structure: Marketplace category description, target inventory type, filter requirements (price range, category, location, ratings), card layout specifications, search and sort behavior.
What Make generated well: The filter sidebar, the product grid with hover states, the search interaction, the sort dropdown.
What needed iteration: The seller detail page needed multiple rounds. The favoriting interaction required explicit prompting for state persistence. Mobile responsiveness took targeted prompts.
Time to shippable prototype: 5-7 hours.
Marketplaces are complex prototypes. Make can build the browse experience well; building the full marketplace (with seller flows, transactions, messaging) hits the limits described in Figma Make Limitations.
Example 6: AI chat interface
The use case: A founder building an AI tool needed a chat interface prototype to demo to investors before committing engineering resources.
Prompt structure: AI chat product description, interface requirements (message bubbles, input area, sidebar with chat history), interaction patterns (streaming text effect, attachment buttons, message regeneration).
What Make generated well: The chat layout with proper message threading, the input area with keyboard shortcuts, the sidebar with chat history list.
What needed iteration: The streaming text effect needed explicit prompting and several iterations. The actual AI integration (calling OpenAI through an Edge Function) required the backend setup workflow.
Time to shippable prototype: 4-6 hours.
AI chat interfaces are a popular Make use case in 2026. The pattern is well-defined enough that Make produces solid first drafts.
Example 7: Multi-step onboarding flow
The use case: A SaaS team building a guided onboarding sequence for new users — collecting role information, customizing the dashboard, walking through key features.
Prompt structure: Onboarding flow, 5-step sequence, progress indicator, save-and-resume capability, personalization based on role selection.
What Make generated well: Individual screens looked good. The progress indicator was clear. The role-selection branching logic worked.
What needed iteration: State persistence between steps was inconsistent. Save-and-resume required explicit backend setup. The flow felt slightly different on each generation — multi-screen consistency is Make's known weakness.
Time to shippable prototype: 5-7 hours, with multi-screen consistency requiring real attention.
Multi-step flows expose Make's biggest current weakness. Single screens are reliable; flows between screens require iteration discipline.
Example 8: Mobile fitness app
The use case: A solo founder building a fitness app prototype — workout library, today's workout view, progress tracking, social features.
Prompt structure: Mobile app context (Make supports mobile-sized previews), screens needed, gesture patterns (swipe to mark complete, pull-to-refresh), visual style (bold typography, energetic palette).
What Make generated well: The today view, the workout library browse experience, the progress tracking charts (using Recharts library which Make can import).
What needed iteration: Gesture interactions needed explicit prompting. The social features (following other users, sharing achievements) required backend setup and iteration.
Time to shippable prototype: 7-9 hours.
Mobile apps are within Make's range but the gesture vocabulary is more limited than web apps. For complex mobile interactions, expect more iteration than equivalent web work.
Example 9: Crypto portfolio tracker
The use case: A designer building a crypto portfolio tool — connected wallet display, token holdings, transaction history, performance charts.
Prompt structure: Crypto product context, dark mode default, dense data layout, real-time data integration (mocked initially), chart requirements.
What Make generated well: The portfolio overview, the holdings table with token logos, the transaction history list, the performance charts using Recharts.
What needed iteration: The wallet connect modal needed multiple states (connecting, connected, error). The chart timeframe switcher required explicit prompting. The mock data needed customization to feel real.
Time to shippable prototype: 5-7 hours.
Crypto interfaces are a known design challenge — data-dense, multiple states, dark mode default. Make handles them better than expected because the patterns are well-documented in its training data.
Example 10: Blog and content hub
The use case: A small team building a marketing blog with category navigation, article pages, author profiles, and newsletter signup.
Prompt structure: Content site framing, blog index with category filter, article page template, author pages, newsletter integration, SEO considerations.
What Make generated well: The blog index, the article page template, the author profile pages, the category filter.
What needed iteration: SEO setup (meta tags, OG images, structured data) required manual code edits. Real content entry took time. Newsletter integration with a real provider (Mailchimp, ConvertKit) required prompting for API integration.
Time to shippable prototype: 4-6 hours for the framework.
Content sites with blogs are a good Make use case because the structure is bounded and well-understood. The content itself is your responsibility.
Example 11: Booking and scheduling app
The use case: A service business building a booking interface — calendar view, time slot selection, customer information form, confirmation flow.
Prompt structure: Booking product context, calendar interaction requirements, time slot display, form fields needed, confirmation email flow.
What Make generated well: The calendar view, the time slot grid, the customer info form, the confirmation screen.
What needed iteration: The actual booking persistence (Supabase database for appointments), the calendar conflict detection logic, the confirmation email setup (via Supabase Edge Function calling SendGrid).
Time to shippable prototype: 6-8 hours including backend.
Booking apps are common Make use cases. The frontend is straightforward; the backend logic for conflict detection and email confirmation takes iteration.
Example 12: Internal HR tool
The use case: A growing company building an internal HR portal — employee directory, time-off requests, performance review submissions, document storage.
Prompt structure: Internal HR tool, role-based access (employees see their own data, managers see their team, HR sees all), specific workflows, document upload requirements.
What Make generated well: The directory layout, the time-off request form, the performance review template, the document upload UI.
What needed iteration: The role-based access control required careful backend setup with Supabase Row Level Security. The approval workflow logic took multiple iteration cycles. Document storage with proper access controls needed explicit prompting.
Time to shippable prototype: 8-12 hours.
HR tools with role-based access push Make's limits. The frontend generates fast; the access control logic and approval workflows require careful prompting and verification.
What patterns emerge across all 12
After collecting these examples, four patterns stand out:
Pattern 1: Bounded use cases win
Make produces better output on bounded use cases (pricing pages, admin dashboards, portfolio sites) than open-ended ones (full SaaS products, complex marketplaces). The clearer the structure, the cleaner the generation.
Pattern 2: Specific prompts compound
Every successful example started with a front-loaded prompt covering what, who, structure, style, and interactions. Vague prompts produced vague output that required heavy iteration. Specific prompts produced output that needed minor iteration.
Pattern 3: Backend examples feel different
Examples with Supabase backends (real auth, real data persistence) feel meaningfully different from static prototypes. They're slower to build but produce more realistic validation. For ideas that depend on user-specific behavior, backend integration is worth the time.
Pattern 4: Multi-screen flows expose limitations
Single-screen examples worked reliably across all 12. Multi-screen flows (onboarding, marketplaces with detail pages, booking sequences) consistently required more iteration. For multi-screen work, expect to spend extra time on consistency across screens.
Common pitfalls visible in real-world examples
Patterns across the examples that often went wrong:
Pitfall 1: Underestimating multi-screen consistency work. Examples 5, 7, and 12 all required noticeably more iteration than initial estimates suggested. Multi-screen flows are Make's known weakness.
Pitfall 2: Skipping backend planning. Examples 2, 9, and 11 all benefited from upfront backend planning. Examples that added backend as an afterthought required more rework.
Pitfall 3: Trying to fit too much into one prompt. The successful examples used iterative refinement after a focused first prompt. Examples that tried to specify everything upfront produced muddled output.
Pitfall 4: Not setting up Make kits early. Examples 1, 3, 5, 10 — the brand-critical ones — all benefited from Make kits configured before the first generation. Examples without kits looked generic.
Get the next article in your inbox
Mantlr publishes one practical, no-fluff article like this every Saturday. Free design resources, evaluation guides, and editorial takes on what's worth using.
Subscribe to Mantlr Editorial →
5,400+ designers and founders. No spam. Unsubscribe anytime.
Frequently asked questions
What can I actually build with Figma Make?
Pricing pages, internal admin dashboards, portfolios, marketplaces (browse experiences), AI chat interfaces, onboarding flows, mobile apps, dashboard tools, blogs, booking systems, and HR tools — among others. Make works best on bounded, well-defined product types. It struggles with open-ended, complex full-stack apps that need production-grade architecture.
How long does a Figma Make project take?
For a simple bounded prototype (pricing page, portfolio): 2-5 hours. For an app with backend integration (habit tracker, marketplace): 5-10 hours. For complex multi-screen apps with role-based access: 8-15 hours. Faster than building from scratch, but not instant.
What are the best Figma Make examples to learn from?
Examples with bounded use cases — pricing pages, admin dashboards, portfolios. They show Make's strengths clearly. Multi-screen flows (onboarding, marketplaces) show Make's limitations and are harder to learn from for beginners.
Can I build a full SaaS product with Figma Make?
You can build a working prototype of a SaaS product, suitable for validation and stakeholder demos. You cannot build production-grade SaaS that ships to real customers without significant manual development beyond what Make produces. For the honest take, see Figma Make Limitations.
What's the biggest mistake people make with Figma Make?
Trying to fit too much into one prompt. The successful examples in this article all used iterative refinement — focused first prompt, then single-change follow-ups. Mega-prompts trying to specify everything produce muddled output.
Should I use Make kits for every project?
For brand-critical work, yes. For throwaway prototypes and quick validation, no. The Make kits setup takes 2-4 hours; for prototypes you'll keep for less than that, the setup isn't worth it.
Can Figma Make build mobile apps?
Yes, with limitations. Make can generate mobile-sized previews and apps that look good on mobile screens. Native mobile interactions (gestures, native components) are harder to specify than web interactions. For pure mobile apps, conventional mobile development tools usually serve better.
Where can I find more Figma Make resources?
Mantlr publishes Figma Make tutorials, comparison guides, and design system integration walkthroughs. See What Is Figma Make?, How to Use Figma Make, and How to Write Better Figma Make Prompts.
What's the cheapest way to try Figma Make?
The Starter (free) Figma plan lets you experiment with Make, though with feature limits. For real work, Professional ($16/seat/month) is the practical minimum. See Figma Make Pricing Explained for the full breakdown.
Are there more advanced Figma Make examples?
Yes — Figma Community has galleries of Make examples that go further than the bounded use cases in this article. They show what's possible but often also show where Make struggles. Browse with realistic expectations.
Build with Mantlr's curated library
You've seen what's possible. The next step is building your own — and finding the design resources that complement your Make workflow.
Mantlr lists 521 designer-vetted free design resources across 43 categories — every one license-verified, production-tested, free of email walls.
Browse Mantlr → · Subscribe to weekly editorial →
Related articles
If you're learning what to build with Figma Make, these articles cover the connected workflow:
- What Is Figma Make? — The foundational article on Make.
- How to Use Figma Make — Full workflow walkthrough.
- How to Write Better Figma Make Prompts — Prompt engineering that produces the examples above.
- Figma Make Limitations — Honest framing of what Make can't do.
- The Complete Guide to Free Design Resources and AI Tools in 2026 — Mantlr's pillar guide to the full resource library.
About Mantlr Editorial
Mantlr is a free directory of designer-vetted, license-verified design resources. We test every resource before listing. No email walls. No paid placements. No affiliate dressing.
This article was written by Mantlr Editorial, the team behind a curated library of 521 free design resources. We work in production design daily and only recommend resources we'd use ourselves.
Last updated: January 2, 2027. Article reviewed quarterly for accuracy.